{"product_id":"edge-ai-qc-kit-real-time-object-detection-on-raspberry-pi-4-and-coral-us","title":"Edge AI QC Kit: Real-Time Object Detection on Raspberry Pi 4 \u0026 Coral USB","description":"\u003ch1\u003eEdge AI QC Kit — Real‑Time Object Detection for Manufacturing With Raspberry Pi 4 \u0026amp; Google Coral USB\u003c\/h1\u003e\n\n\u003cp class=\"value-summary\"\u003eEvery part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.\u003c\/p\u003e\n\n\u003cdiv class=\"specs-strip\"\u003e\n  \u003cspan\u003e\u003cstrong\u003eDifficulty:\u003c\/strong\u003e Intermediate\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eBuild Time:\u003c\/strong\u003e 4–5 hours\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 16–21\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e Edge AI deployment \u0026amp; latency benchmarking\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eWalk into a modern factory floor and you’ll see cameras inspecting products in milliseconds, separating pass from fail without a human ever looking. This kit lets you build that exact system on your desk — a Raspberry Pi 4 outfitted with a Coral USB Accelerator that runs SSD MobileNet, classifying and locating 90 everyday object classes at near‑real‑time speeds. It’s an end‑to‑end computer vision pipeline that doubles as a latency benchmarking lab, giving you a taste of what’s powering Industry 4.0 quality control lines across India.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou’ll assemble a compact computer vision inspection station. A Pi Camera Module 2 captures live video, the Coral USB Accelerator processes every frame with a quantized MobileNet‑SSD model, and you’ll measure exactly how long each inference takes — down to the millisecond. By the end of the 4‑hour build, you’ll have a working system that can identify parts on a conveyor‑like setup and log metrics that an industrial engineer would actually use. The benchmarking scripts also teach you what “inference latency” means when you push 30 FPS through an edge TPU.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eDeploy a quantized SSD MobileNet object detection model on the Coral USB Edge TPU\u003c\/li\u003e\n  \u003cli\u003eConfigure Raspberry Pi 4 for high‑speed camera inference with the Pi Camera Module 2\u003c\/li\u003e\n  \u003cli\u003eMeasure and compare inference latency between CPU‑only and Edge TPU‑accelerated pipelines\u003c\/li\u003e\n  \u003cli\u003eInterpret detection outputs (bounding boxes, class labels, confidence scores) in a manufacturing QC context\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eKit Contents\u003c\/h2\u003e\n\u003ctable\u003e\n  \u003cthead\u003e\u003ctr\u003e\n\u003cth\u003eComponent\u003c\/th\u003e\n\u003cth\u003eQuantity\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n  \u003ctbody\u003e\n    \u003ctr\u003e\n\u003ctd\u003eRaspberry Pi 4 Model B 4GB\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eCoral USB Accelerator\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePi Camera Module 2\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eMicroSD Card 32GB\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eUSB-C PSU\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n  \u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eWhy Buy This Kit Instead of Sourcing Parts Separately\u003c\/h2\u003e\n\u003ctable\u003e\n  \u003cthead\u003e\u003ctr\u003e\n\u003cth\u003eFactor\u003c\/th\u003e\n\u003cth\u003eSourcing Separately\u003c\/th\u003e\n\u003cth\u003eCompoden Kit\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n  \u003ctbody\u003e\n    \u003ctr\u003e\n\u003ctd\u003eCompatibility checks\u003c\/td\u003e\n\u003ctd\u003eYou verify every part\u003c\/td\u003e\n\u003ctd\u003ePre-tested as a system\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eBuild support\u003c\/td\u003e\n\u003ctd\u003eForums and scattered tutorials\u003c\/td\u003e\n\u003ctd\u003eAI companion trained on this exact project\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eTime to first working build\u003c\/td\u003e\n\u003ctd\u003eDays of debugging\u003c\/td\u003e\n\u003ctd\u003eHours, with step-by-step guidance\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eShipping coordination\u003c\/td\u003e\n\u003ctd\u003eMultiple sellers, multiple delays\u003c\/td\u003e\n\u003ctd\u003eOne shipment from Bengaluru in 3-5 days\u003c\/td\u003e\n\u003c\/tr\u003e\n  \u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eWho This Kit Is For\u003c\/h2\u003e\n\u003cp\u003eDesigned for B.Tech ECE\/EEE students, Smart India Hackathon teams crafting defect detection prototypes, and ATL Tinkering Lab mentors who want to move beyond basic Arduino projects. It’s also a natural fit for anyone preparing for VIT, BITS, or NIT project submissions where real‑time embedded AI makes a strong impression.\u003c\/p\u003e\n\n\u003ch2\u003eBuilt and Backed by Compoden\u003c\/h2\u003e\n\u003cp\u003eEvery Compoden kit ships with an AI build companion trained on this exact project — accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.\u003c\/p\u003e\n\n\u003cdetails\u003e\u003csummary\u003eWhat if I get stuck during the build?\u003c\/summary\u003e\u003cp\u003eScan the QR code inside the box to get instant, step‑by‑step answers from our AI companion, or drop a WhatsApp message to our Bengaluru support team.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I train the model to recognise my own objects?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The Coral USB works with TensorFlow Lite models, and we include instructions to retrain MobileNet‑SSD on custom datasets using Google Colab — perfect if you need to detect electronic components, packaging defects, or inventory items.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eHow do I benchmark latency?\u003c\/summary\u003e\u003cp\u003eOur pre‑installed Python scripts timestamp every inference cycle and save results to a CSV file. You’ll be able to compare CPU-only vs. Edge TPU speeds and see exactly how Coral delivers sub‑30 ms object detection on the Pi 4.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eIs this kit suitable for a CBSE Class 12 computer science project?\u003c\/summary\u003e\u003cp\u003eYes, if you have some prior Python and Raspberry Pi experience. The QC‑focused narrative aligns well with emerging tech project requirements and the latency lab fits into an evaluation section perfectly.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eManufacturing QC — SSD MobileNet on Google Coral USB detects 90 object classes at near real-time speeds on Pi 4 — latency benchmarking lab.\u003c\/p\u003e\n  \u003ch4\u003eWhat's in this kit\u003c\/h4\u003e\n  \u003cul\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/industrial-ph-sensor-module-for-arduino-esp32-raspberry-pi\"\u003eRaspberry Pi 4 Model B 4GB\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003eCoral USB Accelerator\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/4-channel-relay-board-for-esp32-30-pin-5v-control\"\u003ePi Camera Module 2\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/microsd-card-reader-spi-module-for-arduino\"\u003eMicroSD Card 32GB\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/raspberry-pi-4-official-power-supply-5v-3a-usb-c-compoden\"\u003eUSB-C PSU\u003c\/a\u003e\u003c\/li\u003e\n  \u003c\/ul\u003e\n\u003c\/div\u003e\n\n\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What is included in the Manufacturing QC Vision Pro Kit with Raspberry Pi 4 + Camera?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Manufacturing QC Vision Pro Kit with Raspberry Pi 4 + Camera includes all components needed: Raspberry Pi 4 Model B 4GB, Coral USB Accelerator, Pi Camera Module 2, MicroSD Card 32GB, USB-C PSU and more. 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